[eng] This document is centered on the task of synchronizing and correcting data given by two fusion filter systems ¿ the project¿s fusion algorithm and the reference ¿ installed in a test car. Eventually, this task evolves ...[+]

[eng] This document is centered on the task of synchronizing and correcting data given by two fusion filter systems ¿ the project¿s fusion algorithm and the reference ¿ installed in a test car. Eventually, this task evolves in synchronizing these two sets of data with other car¿s two.
The motivation of the entire project is to develop a fusion filter algorithm that achieves improving the positioning accuracy of current GPS receivers. Since as soon as the system is ready, the objective is installing it in every kind of car, it must be as cheaper as it is possible. Therefore, it only uses sensors that are already installed in every current car, working standalone for other control systems like ABS, ESP, etc. The fusion algorithm is already designed based on the signals offered by an IMU, which fuses with other sensors¿ signals, from a GPS receiver, odometers and a steering wheel sensor. However, the algorithm is not completely developed yet, as it presents errors calculating some of the required outputs. The debugging of the algorithm needs its signals completely synchronized in time with the ones from the reference, so that the developer is able to compare them to find their differences and, therefore, the errors.
For the comparison of the signals from the fusion algorithm and the reference, a common time system is needed. Since they are calculated on two non-communicated systems, the only way of performing the time synchronization is by using the time values from the GPS timestamps, which are an absolute time system.
The other major issue is that the equivalent signals from the two systems present a lag time due to the difference in calculation speed of their fusion algorithms. The chosen way for correcting this lag time is a cross-correlation study method, shifting the signals to find the better correlation coefficient. That also gives early information of whether the studied signals have been correctly calculated or not by the fusion algorithm. Once the lag correction is done to every pair of signals, it becomes possible to compare each output signal with its equivalent from the reference system, in order to determine the proper calculation of the signals by the fusion algorithm.
The result of the lag correction is the complete synchronization of the two sets of data with the same time reference system. For the task of synchronizing two test cars, the two sets of data from each car are synchronized together in a similar way than before.
Concerning the development of the algorithm for the synchronization of a single test car; it has been completed, since it is being used by other developers within the project for testing filter configurations and debugging errors.
The development of the algorithm for two test cars data has been completed as far as it can be without having tested it with real simultaneous measurements. However, the code has been tested for two equal measurements retarded by software.
The fusion algorithm needs more development in order to solve some issues on the signals estimation. So, the work done with the synchronization should be helpful to debug the algorithm.[-]